Current Advanced Driver Assistance Systems (ADAS) and automated driving system use multiple sensors, such as camera, radar, and LiDAR, to detect objects in the proximity of the vehicle. The sensors use features such as intensity, range, color etc. to detect objects. Range value describing the distance to point in the scene is critical for the success and reliability of object detection. Range values can be combined to generate a 2-D range-map showing the distance to points in a scene from a specific point. Range-map normally associated with a sensor device such as camera or LiDAR. If the sensor is probably calibrated, range values can be given directly in feet or meters.
A single camera can be used to create generate range information using structure from motion. This typically results in sparse range estimation that may not be accurate especially for dynamic objects. Stereo camera or multiple camera setup system can also be used but add cost to the system in both hardware, since it uses multiple cameras and need to be probably calibrated, and in software since stereo range estimation is an expensive and error prone process. LiDAR has been the most widely used sensor for range estimation but is currently expensive for most applications, and limited in range it can measure.